Cross-Domain Text Mining to Predict Adverse Events from Tyrosine Kinase Inhibitors for Chronic Myeloid Leukemia

• Authors: Nidhi Mehra, Emory University; Armon Varmeziar, Emory University; Xinyu Chen, Emory University; Olivia Kronick, Emory University; Rachel Fisher, Emory University; Vamsi Kota, Emory University; Cassie Mitchell, Emory University
• Journal Title: CANCERS
• Volume: Volume 14, Number 19
• Publisher: MDPI | 2022-10-01
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.3390/cancers14194686
• Subjects: Health Sciences, Pathology; Health Sciences, Oncology
• Keywords: Science & Technology; Life Sciences & Biomedicine; Oncology; chronic myeloid leukemia; tyrosine kinase inhibitor; BCR ABL; adverse event; side effect; toxicity; heterogeneous information network; machine learning; natural language processing; CHRONIC MYELOGENOUS LEUKEMIA; IMATINIB THERAPY; CML PATIENTS; DASATINIB; NILOTINIB; MALIGNANCIES; FRONTLINE; EFFICACY; RESISTANCE; REMISSION

Abstract

Tyrosine kinase inhibitors (TKIs) are prescribed for chronic myeloid leukemia (CML) and some other cancers. The objective was to predict and rank TKI-related adverse events (AEs), including under-reported or preclinical AEs, using novel text mining. First, k-means clustering of 2575 clinical CML TKI abstracts separated TKIs by significant (p < 0.05) AE type: gastrointestinal (bosutinib); edema (imatinib); pulmonary (dasatinib); diabetes (nilotinib); cardiovascular (ponatinib). Next, we propose a novel cross-domain text mining method utilizing a knowledge graph, link prediction, and hub node network analysis to predict new relationships. Cross-domain text mining of 30+ million articles via SemNet predicted and ranked known and novel TKI AEs. Three physiology-based tiers were formed using unsupervised rank aggregation feature importance. Tier 1 ranked in the top 1%: hematology (anemia, neutropenia, thrombocytopenia, hypocellular marrow); glucose (diabetes, insulin resistance, metabolic syndrome); iron (deficiency, overload, metabolism), cardiovascular (hypertension, heart failure, vascular dilation); thyroid (hypothyroidism, hyperthyroidism, parathyroid). Tier 2 ranked in the top 5%: inflammation (chronic inflammatory disorder, autoimmune, periodontitis); kidney (glomerulonephritis, glomerulopathy, toxic nephropathy). Tier 3 ranked in the top 10%: gastrointestinal (bowel regulation, hepatitis, pancreatitis); neuromuscular (autonomia, neuropathy, muscle pain); others (secondary cancers, vitamin deficiency, edema). Results suggest proactive TKI patient AE surveillance levels: regular surveillance for tier 1, infrequent surveillance for tier 2, and symptom-based surveillance for tier 3.